Cultural Research

1. Cultural Research Západočeská Univerzita (ZČU) James Boster

2. Sources of Anthropological Data Západočeská Univerzita (ZČU) James Boster

3. Artifacts

4. Documents

5. Behavioral Observation

6. Participant Observation

7. Interviews

8. Systematic Data Collection Západočeská Univerzita (ZČU) James Boster

9. Goal • Data for the quantitative comparison & aggregation of individual responses. • Information to build a data matrix.

10. Basic Concepts and Definitions Západočeská Univerzita (ZČU) James Boster

12. Guiding Metaphor • Data sets are spaces with a Cartesian coordinate system. • Variables are the space’s dimensions. • Cases are points in the space or the endpoints of vectors from the origin. • Data place all points on all dimensions.

13. Array • An ordered arrangement of data elements. • a vector is a one-dimensional array • a matrix is a two-dimensional array

14. Vector • A magnitude and a direction in multidimensional space. • A one-dimensional array.

16. Matrix • A set of vectors which define a multidimensional space. • A two-dimensional array with more than one row and column.

17. Matrix • columns = dimensions = variables • rows = vectors = points = cases

19. Indices/Subscripts • Numbers which specify the row and column of a cell in a matrix.

21. Conventions • Matrices have m rows and n columns. • The variable i indexes the rows, and the variable j indexes the columns. • If the matrix is stored in M, each cell is indexed as M[i,j]; with row subscript first and column subscript second.

22. Conventions • Matrices are typically accessed the way we read a page in a book. • first, left to right across each line. • next, top to bottom down the page.

23. Types of Matrices • Square vs. rectangular • equal or unequal number of rows and columns. • Symmetrical vs. asymmetrical • either equal or unequal to its transpose. • Similarity vs. distance • high values are either close or far.

24. Square Matrix

25. Rectangular Matrix

26. Symmetrical Matrices

27. Asymmetrical Matrices

28. Similarity Matrix

29. Distance Matrix

30. Structured elicitation • Similarity judgment • Freelists • Identification • Frame substitution tasks • Ranking and rating

31. Domains • Facial expression of emotion • Color classification • Acts of destruction • Emotionally evocative situations • Locomotion

32. Similarity Judgments

33. Why elicit similarity judgments? • The judgment of similarity and difference is a fundamental cognitive process that other cognitive acts of cultural interest depend on: • same/different judgments • categorization and classification • propositional knowledge • decision making • theory (or cultural model) construction

34. Why elicit similarity judgments? • Can give quick overview of a domain • A’ara personality descriptors (White) • as map

36. Why elicit similarity judgments? • Can give quick overview of a domain • A’ara personality descriptors (White) • as map • as cluster diagram

40. Why elicit similarity judgments? • Can give quick overview of a domain • A’ara personality descriptors (White) • as map • as cluster diagram • students' gender role terms (Holland and Skinner) • males

42. Why elicit similarity judgments? • Can give quick overview of a domain • A’ara personality descriptors (White) • as map • as cluster diagram • students' gender role terms (Holland and Skinner) • male map • female map

44. Why elicit similarity judgments? • Can reveal differences between groups • Atlantic fish (Boster & Johnson) • novice student map

46. Why elicit similarity judgments? • Can reveal differences between groups • Atlantic fish (Boster & Johnson) • novice student map • expert recreational fisherman map

48. Why elicit similarity judgments? • Can reveal similarities between groups • personality descriptors • A’ara • Oriya • US.